Signal Processing
This data contains fatigue and non-fatigue sEMG data of four motions shoulder flexion (SF), shoulder abduction (SA) and elbow extension (EE) and wrist flexion & extension (WFE).
The file has two subfiles: WFE and shoulders. The "shoulders" has sEMG data of three motions while the WFE subfile has sEMG data of different adjecent matrices. The feature matrices are processed by Boruta.
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52 Views
The proposed GAT-based channel estimation method examines the performance of the DtS IoT networks for different RIS configurations to solve the challenging channel estimation problem. It is shown that the proposed GAT both demonstrates a higher performance with increased robustness under changing conditions and has lower computational complexity compared to conventional deep learning methods.
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767 Views
The accuracy and reliability of an Ultra- WideBand (UWB) Indoor Positioning System (IPS) are compromised owing to the positioning error caused by the Non-Line-of-Sight (NLoS) signals. To address this, Machine Learning (ML) has been employed to classify Line-of-Sight (LoS) and NLoS components. However, the performance of ML algorithms degrades due to the disproportion of the number of LoS and NLoS signal components. A Weighted Naive Bayes (WNB) algorithm is proposed in this paper to mitigate this issue.
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312 Views
This dataset contains the raw data to figure 6 of the paper "Modeling and evaluation of a rate-based transcutaneous blood gas monitor" that has been submitted to IEEE Transactions on Biomedical Engineering
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150 Views
This dataset corresponds to the measurements of a monostatic microwave imaging system, collected using the facility described in [1].
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347 Views
The human gait is unique and so is the impact of a walking human on the propagation of wireless signals within a wireless network. Using appropriate pattern recognition techniques, a person can thus be identified just from a time series of Received Signal Strength (RSS) measurements. This dataset holds bidirectional RSS measurements recorded within a mesh network of four Bluetooth sensor devices. During the measurements, a total of 14 subjects walked individually through the setup. A total of more than 10,000 recordings are provided.
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621 Views
The Bluetooth 5.1 Core Specification brought Angle of Arrival (AoA) based Indoor Localization to the Bluetooth Standard. This feature is usually referred to as Bluetooth Direction Finding. Besides localization, this new technology can be used to implement a radar system just using commodity Bluetooth chipsets. This dataset holds measurements recorded using a demonstration setup for such kind of radar system. Along with this dataset, the experimental setup, the used sensor devices, and the structure of the provided data files are described in detail.
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360 Views
The drawback of inter-subcarrier interference in OFDM systems makes the channel estimation and signal detection performance of OFDM systems with few pilots and short cyclic prefixes (CP) poor. Thus, we use deep learning to assist OFDM in recovering nonlinearly distorted transmission data. Specifically, we use a self-normalizing network (SNN) for channel estimation, combined with a convolutional neural network (CNN) and a bidirectional gated recurrent unit (BiGRU) for signal detection, thus proposing a novel SNN-CNN-BiGRU network structure (SCBiGNet).
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216 Views
The data collection questionnaire consisted of two sections. One section involved the collection of data via Google Forms questionnaires, and the other involved the collection of WhatsApp voice samples. There were three subsections in the questionnaire section. The first consisted of the individual's basic information, such as email address, name, and identification number. The second was the personal health questionnaire depression scale (PHQ8), which included 8 groups of statements, and the third was the Beck Depression Inventory-II, which contained 21 groups of statements.
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820 Views
<p>Two-electrode straight open magnetic source (TSOMS) has been widely used on the magnetic minesweeper and magnetic decoy. Fast-forward modeling and obtaining the high-precision magnetic field in the air are the prerequisites for real-time inversion and positioning of the TSOMS. In this paper, we propose an algorithm to calculate the magnetic field of the two-electrode straight open magnetic source (MFTSOMS) by previous theoretical research. And a classical algorithm of electric dipole magnetic field is used to verify the correctness of our algorithm.
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84 Views